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Integrative single-cell and bulk transcriptomics with reverse network pharmacology prioritizes macrophage-associated
Yan Dong1,2, Yanshuang Luo3, Yantong Chen3
1Department of Pain Medicine, The Affiliated Anning First People's Hospital of Kunming University of Science and Technology, Kunming, Yunnan, China.
Introduction:
Lyme arthritis (LA) involves complex immune dysregulation, and macrophages contribute centrally to persistent joint inflammation. However, synovial macrophage heterogeneity and its potential relevance to therapeutic intervention remain incompletely defined.
Methods:
We integrated scRNA-seq data from Borrelia burgdorferi (Bb)-infected murine joints (GSE233850) with bulk RNA-seq data (GSE283617). The workflow included Seurat clustering, Monocle 3 trajectory inference, CellChat communication analysis, and functional enrichment. We constructed a PPI network from intersecting genes and applied five complementary topological measures to prioritize consensus hubs. Candidate gene expression was evaluated in an external transcriptomic dataset (GSE63085) and by qRT-PCR. CTD-based association analysis and molecular docking were used to prioritize candidate compounds. Virtual knockout analysis explored the potential regulatory effects of hub genes.
Results:
The two pooled libraries differed descriptively in the relative representation of nine major cell populations. Among macrophages/monocytes, we resolved seven marker-defined states. Monocle 3 trajectories were rooted at Classical_Inflam_Mono, and CellChat highlighted Tgfb1-(Tgfbr1+Tgfbr2) as a prominent inferred TGF-β axis. Intersecting GSE283617 with GSE233850 yielded 121 shared genes, and GSEA showed negative enrichment of oxidative phosphorylation during infection. Mrc1 and Msr1 were the only genes ranked among the top 10 by all five measures: Degree, Bottleneck, EcCentricity, MNC, and MCC. Across these complementary analyses, Msr1 emerged as a candidate Bb-responsive gene potentially relevant to LA. A CTD-based source-compound-gene network and molecular docking prioritized curcumin and demethoxycurcumin for future experimental testing.
Conclusion:
These findings provide an exploratory atlas of macrophage transcriptional states in the analyzed LA model and identify Msr1 as a candidate infection-responsive gene. Its disease specificity and clinical utility require validation in joint-derived specimens from patients with clinically confirmed LA. The computationally prioritized compounds remain hypotheses that require direct binding and functional testing.